Colorectal cancer (CRC) is the fourth most frequently diagnosed cancer and accounts for the second largest number of cancer deaths in Western societies. One of the major molecular targets to arrise over the last decade is the epidermal growth factor receptor (EGFR), a major mitogenic signal receptor used by many epithelial cell types. Supporting the importance of EGFR in CRC development, we and others have observed that inhibition of EGFR dramatically attenuates development of intestinal and colorectal tumors in the ApcMin mouse model. Yet, some tumors still arise, even with significant reductions in EGFR activity, implying the existence of compensatory mechanisms for the loss of EGFR. This observation is particularly relevant to human cancer therapy since no validated biomarkers or unique gene expression signatures exist that can partition CRCs based upon their likely sensitivity to EGFR inhibitors. Mouse models offer the potential to define the context and biomarkers for tumors likely to respond to EGFR inhibitor therapy. Equally importantly, mouse models have the potential to identify compensatory signaling networks utilized in the context of reduced EGFR activity, which will make excellent therapeutic targets for cancers resistant to EGFR inhibitor therapy. Other Egfr/Erbb-related genes are also expressed in CRCs, driving the development of pan-ERBB inhibitor therapies. However, scant data exists defining the in vivo functional role of Erbb genes during CRC development or their relationship to EGFR during tumorigenesis. We are uniquely positioned to address many of these open questions by exploiting several new mouse models we developed. These models are ideally suited to develop a gene expression biomarker for sensitivity to EGFR inhibition, to investigate the compensatory networks used by cancers when EGFR is inhibited, identifying leads for new therapeutic targets in cancers resistant to anti-EGFR therapy, and to expose the role and functional interactions among the Erbb genes during CRC development. PUBLIC HEALTH RELEVANCE: The identification of biomarkers that indicate which patients will respond to specific molecular-targeted therapies like those against EGFR is highly significant and relevant to improving the efficacy of clinical treatments. Similarly, the identification of pathways that compensate for the loss of targeted pathways offers in targets to improve therapeutic benefit. The use of novel mouse models as proposed in this application has the potential to provide these insights. [unreadable] [unreadable] [unreadable]